14 citations · 32 across the 11 of their papers we have counts for
11 papers
Hard-Negative Sampling for Contrastive Learning: Optimal Representation Geometry and Neural- vs Dimensional-Collapse
Ruijie Jiang, Thuan Nguyen, Shuchin Aeron +1
For a widely-studied data model and general loss and sample-hardening functions we prove that the losses of Supervised Contrastive Learning (SCL), Hard-SCL (HSCL), and Unsupervised…
A principled approach to model validation in domain generalization
Boyang Lyu, Thuan Nguyen, Matthias Scheutz +2
Domain generalization aims to learn a model with good generalization ability, that is, the learned model should not only perform well on several seen domains but also on unseen dom…
Trade-off between reconstruction loss and feature alignment for domain generalization
Thuan Nguyen, Boyang Lyu, Prakash Ishwar +2
Domain generalization (DG) is a branch of transfer learning that aims to train the learning models on several seen domains and subsequently apply these pre-trained models to other…
Supervised Contrastive Learning with Hard Negative Samples
Ruijie Jiang, Thuan Nguyen, Prakash Ishwar +1
Through minimization of an appropriate loss function such as the InfoNCE loss, contrastive learning (CL) learns a useful representation function by pulling positive samples close t…
Joint covariate-alignment and concept-alignment: a framework for domain generalization
Thuan Nguyen, Boyang Lyu, Prakash Ishwar +2
In this paper, we propose a novel domain generalization (DG) framework based on a new upper bound to the risk on the unseen domain. Particularly, our framework proposes to jointly…
Conditional entropy minimization principle for learning domain invariant representation features
Thuan Nguyen, Boyang Lyu, Prakash Ishwar +2
Invariance-principle-based methods such as Invariant Risk Minimization (IRM), have recently emerged as promising approaches for Domain Generalization (DG). Despite promising theory…
Barycentric-alignment and reconstruction loss minimization for domain generalization
Boyang Lyu, Thuan Nguyen, Prakash Ishwar +2
This paper advances the theory and practice of Domain Generalization (DG) in machine learning. We consider the typical DG setting where the hypothesis is composed of a representati…
VinaFood21: A Novel Dataset for Evaluating Vietnamese Food Recognition
Thuan Trong Nguyen, Thuan Q. Nguyen, Dung Vo +5
Vietnam is such an attractive tourist destination with its stunning and pristine landscapes and its top-rated unique food and drink. Among thousands of Vietnamese dishes, foreigner…
Single-bit Quantization Capacity of Binary-input Continuous-output Channels
Thuan Nguyen, Thinh Nguyen
We consider a channel with discrete binary input X that is corrupted by a given continuous noise to produce a continuous-valued output Y. A quantizer is then used to quantize the c…
On the Uniqueness of Binary Quantizers for Maximizing Mutual Information
Thuan Nguyen, Thinh Nguyen
We consider a channel with a binary input X being corrupted by a continuous-valued noise that results in a continuous-valued output Y. An optimal binary quantizer is used to quanti…
Entropy-Constrained Maximizing Mutual Information Quantization
Thuan Nguyen, Thinh Nguyen
In this paper, we investigate the quantization of the output of a binary input discrete memoryless channel that maximizing the mutual information between the input and the quantize…